2026-07-23T16:56:26Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:7165 2024-03-06T10:39:53Z ddc:004 open_access

Semi-Partitioned Scheduling of Dynamic Real-Time Workload: A Practical Approach Based on Analysis-Driven Load Balancing Casini, Daniel Biondi, Alessandro Buttazzo, Giorgio Semi-partitioned scheduling dynamic workload real-time Recent work showed that semi-partitioned scheduling can achieve near-optimal schedulability performance, is simpler to implement compared to global scheduling, and less heavier in terms of runtime overhead, thus resulting in an excellent choice for implementing real-world systems. However, semi-partitioned scheduling typically leverages an off-line design to allocate tasks across the available processors, which requires a-priori knowledge of the workload. Conversely, several simple global schedulers, as global earliest-deadline first (G-EDF), can transparently support dynamic workload without requiring a task-allocation phase. Nonetheless, such schedulers exhibit poor worst-case performance. This work proposes a semi-partitioned approach to efficiently schedule dynamic real-time workload on a multiprocessor system. A linear-time approximation for the C=D splitting scheme under partitioned EDF scheduling is first presented to reduce the complexity of online scheduling decisions. Then, a load-balancing algorithm is proposed for admitting new real-time workload in the system with limited workload re-allocation. A large-scale experimental study shows that the linear-time approximation has a very limited utilization loss compared to the exact technique and the proposed approach achieves very high schedulability performance, with a consistent improvement on G-EDF and pure partitioned EDF scheduling. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Daniel Casini and Alessandro Biondi and Giorgio Buttazzo 2017 Is Part Of LIPIcs, Volume 76, 29th Euromicro Conference on Real-Time Systems (ECRTS 2017) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.ECRTS.2017.13 urn:nbn:de:0030-drops-71659 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2017.13 eng https://creativecommons.org/licenses/by/3.0/legalcode